Statistical semantics methods and applications / Sverker Sikstro̘m, Danilo Garcia, editor.

Format:

Book

Contributor:

Sikstro̘m, Sverker.

Garcia, Danilo, 1973-

ProQuest ebook central.

Language:

English

Subjects (All):

Semantics--Statistical methods.

Semantics.

Physical Description:

1 online resource (266 pages)

Place of Publication:

Cham : Springer, 2020.

System Details:

text file

Contents:

Intro

Preface

Acknowledgment

Contents

Contributors

Part I: Methods

Chapter 1: Introduction to Statistical Semantics

References

Chapter 2: Creating Semantic Representations

Vector Space Model

Feature Hashing

Random Indexing

Latent Semantic Analysis

Non-negative Matrix Factorization

Explicit Semantic Analysis

Word Embeddings

Deep Learning Representations

Creating Explicit Semantic Representations

Creating Semantic Representations with Non-linguistic Information

Evaluating Semantic Representations

Word Similarity/Relatedness

Verbal Analogies

Word Intrusion

Sentiment Analysis

Challenges: Polysemy, Homograph, Bias and Compounds

What Does It Mean?

Chapter 3: Software for Creating and Analyzing Semantic Representations

Introduction

Natural Language Processing Toolkit, NLTK

spaCy

Pattern

Polyglot

MediaWiki Processing Software

Scikit-Learn

Word Embedding

Word2vec

GloVe

FastText

Other Word Embedding Software

Other Embedding Software

Gensim

Deep Learning

Keras

Explicit Creation of Semantic Representations

References

Chapter 4: Semantic Similarity Scales: Using Semantic Similarity Scales to Measure Depression and Worry

Semantic Analysis Methods

Using the Semantic Representations to Measure Semantic Similarity

Applying High Quality Semantic Representations to Experimental Data

Adding Semantic Representations Together to Represent Several Words or a Text

Understanding Semantic Similarity

Semantic t-Tests Computed on Semantic Similarities

Research Study

Assessing Psychological Constructs Using Semantic Similarity Scales: Measuring, Describing and Differentiating Depression and ...

The Semantic Measures Approach: Semantic Questions and Word Norms

Measuring Constructs: Unipolar and Bipolar Semantic Similarity Scales

Describing Constructs Using Plots

Differentiating Between Constructs: Inter-Correlations and Covarying Variables in Plots

Method

Participants

Measures and Material

Procedure

Statistical Analyses

Results

Semantic Responses Differ Significantly

Measuring Psychological Constructs

Bipolar Scales Yield Stronger Correlations to Rating Scales than Unipolar Scales

Describing Psychological Constructs

Semantic Similarity Scales Differentiate Better Between Depression and Worry than Rating Scales

Discussion

Unipolar and Bipolar Scales

Limitations and Future Research

Concluding Remarks

Chapter Summary

Step-by-Step Computational Guides

Chapter 5: Prediction and Semantic Trained Scales: Examining the Relationship Between Semantic Responses to Depression and Wor...

Using the Semantic Representations to Predict Numerical Values

Using the Semantic Representations in Multiple Linear Regression

Notes:

Description based upon print version of record.

Cross Validation Using a Training-Set and a Test-Set

Electronic reproduction. Ann Arbor, MI Available via World Wide Web.

Other Format:

Print version: Sikstro̘m, Sverker Statistical Semantics : Methods and Applications

ISBN:

9783030372507

3030372502

Publisher Number:

40030099312

10.1007/978-3-030-37

Access Restriction:

Restricted for use by site license.